• DocumentCode
    3304059
  • Title

    Early experiments on the CAM-Brain Machine (CBM)

  • Author

    De Garis, Hugo ; De Penning, Leo ; Buller, Andrzej ; Decesare, Derek

  • Author_Institution
    Brain Builder Group, STARLAB, Brussels, Belgium
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    211
  • Lastpage
    219
  • Abstract
    This paper presents results of some of the first evolution experiments undertaken on an actual CAM-Brain Machine (CBM), using the hardware itself and not software simulations. A CBM is a specialised piece of programmable (evolvable) hardware that uses Xilinx XC6264 programmable FPGA chips to grow and evolve, at electronic speeds, 3D cellular automata (CA) based neural network circuit modules of some 1000 neurons each. A complete run of a genetic algorithm (e.g. with 100 generations and a population size of 100) is executed in a few seconds. 64000 of these modules can be evolved separately according to the fitness definitions of human “EEs” (evolutionary engineers) and downloaded one by one into a gigabyte of RAM. Human “BAs” (brain architects) then interconnect these modules “by hand” according to their artificial brain architectures. The CBM then updates the binary neural signaling of the artificial brain (with 64000 “hand” interconnected modules, i.e. 75 million neurons) at a rate of 130 billion CA cell updates a second, which is fast enough for real time control of robots. Before such multi-moduled artificial brains can be constructed. It is essential that the quality of the evolution (the “evolvability”) of individual modules be adequate. This paper reports on the first evolution results obtained on CBM hardware
  • Keywords
    cellular automata; evolutionary computation; neural net architecture; reconfigurable architectures; CAM-Brain Machine; CBM; CBM hardware; Xilinx XC6264 programmable FPGA chips; cellular automata; evolution experiments; neural network circuit modules; Biological neural networks; Cellular neural networks; Circuit simulation; Field programmable gate arrays; Genetic algorithms; Humans; Integrated circuit interconnections; Neural network hardware; Neural networks; Neurons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolvable Hardware, 2001. Proceedings. The Third NASA/DoD Workshop on
  • Conference_Location
    Long Beach, CA
  • Print_ISBN
    0-7695-1180-5
  • Type

    conf

  • DOI
    10.1109/EH.2001.937964
  • Filename
    937964